A Harmonised Approach to Curating Research-Ready Datasets for Asthma, Chronic Obstructive Pulmonary Disease (COPD) and Interstitial Lung Disease (ILD) in England, Wales and Scotland Using Clinical Practice Research Datalink (CPRD), Secure Anonymised Information Linkage (SAIL) Databank and DataLoch.

Background: Electronic healthcare records (EHRs) are an important resource for health research that can be used to improve patient outcomes in chronic respiratory diseases. However, consistent approaches in the analysis of these datasets are needed for coherent messaging, and when undertaking comparative studies across different populations. Methods and Results: We developed a harmonised curation approach to generate comparable patient cohorts for asthma, chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) using datasets from within Clinical Practice Research Datalink (CPRD; for England), Secure Anonymised Information Linkage (SAIL; for Wales) and DataLoch (for Scotland) by defining commonly derived variables consistently between the datasets. By working in parallel on the curation methodology used for CPRD, SAIL and DataLoch for asthma, COPD and ILD, we were able to highlight key differences in coding and recording between the databases and identify solutions to enable valid comparisons. Conclusion: Codelists and metadata generated have been made available to help re-create the asthma, COPD and ILD cohorts in CPRD, SAIL and DataLoch for different time periods, and provide a starting point for the curation of respiratory datasets in other EHR databases, expediting further comparable respiratory research.

Common governance model: a way to avoid data segregation between existing trusted research environment.

Background: Trusted Research Environments provide a legitimate basis for data access along with a set of technologies to support implementation of the "five-safes" framework for privacy protection. Lack of standard approaches in achieving compliance with the "five-safes" framework results in a diversity of approaches across different TREs. Data access and analysis across multiple TREs has a range of benefits including improved precision of analysis due to larger sample sizes and broader availability of out-of-sample records, particularly in the study of rare conditions. Knowledge of governance approaches used across UK-TREs is limited. Objective: To document key governance features in major UK-TRE contributing to UK wide analysis and to identify elements that would directly facilitate multi TRE collaborations and federated analysis in future. Method: We summarised three main characteristics across 15 major UK-based TREs: 1) data access environment; 2) data access requests and disclosure control procedures; and 3) governance models. We undertook case studies of collaborative analyses conducted in more than one TRE. We identified an array of TREs operating on an equivalent level of governance. We further identify commonly governed TREs with architectural considerations for achieving an equivalent level of information security management system standards to facilitate multi TRE functionality and federated analytics. Results: All 15 UK-TREs allow pooling and analysis of aggregated research outputs only when they have passed human-operated disclosure control checks. Data access requests procedures are unique to each TRE. We also observed a variability in disclosure control procedures across various TREs with no or minimal researcher guidance on best practices for file out request procedures. In 2023, six TREs (40.0%) held ISO 20071 accreditation, while 9 TREs (56.2%) participated in four-nation analyses. Conclusion: Secure analysis of individual-level data from multiple TREs is possible through existing technical solutions but requires development of a well-established governance framework meeting all stakeholder requirements and addressing public and patient concerns. Formation of a standard model could act as the catalyst for evolution of current TREs governance models to a multi TRE ecosystem within the UK and beyond.

Investigating the uptake, effectiveness and safety of COVID-19 vaccines: protocol for an observational study using linked UK national data.

INTRODUCTION: The novel coronavirus SARS-CoV-2, which emerged in December 2019, has caused millions of deaths and severe illness worldwide. Numerous vaccines are currently under development of which a few have now been authorised for population-level administration by several countries. As of 20 September 2021, over 48 million people have received their first vaccine dose and over 44 million people have received their second vaccine dose across the UK. We aim to assess the uptake rates, effectiveness, and safety of all currently approved COVID-19 vaccines in the UK. METHODS AND ANALYSIS: We will use prospective cohort study designs to assess vaccine uptake, effectiveness and safety against clinical outcomes and deaths. Test-negative case-control study design will be used to assess vaccine effectiveness (VE) against laboratory confirmed SARS-CoV-2 infection. Self-controlled case series and retrospective cohort study designs will be carried out to assess vaccine safety against mild-to-moderate and severe adverse events, respectively. Individual-level pseudonymised data from primary care, secondary care, laboratory test and death records will be linked and analysed in secure research environments in each UK nation. Univariate and multivariate logistic regression models will be carried out to estimate vaccine uptake levels in relation to various population characteristics. VE estimates against laboratory confirmed SARS-CoV-2 infection will be generated using a generalised additive logistic model. Time-dependent Cox models will be used to estimate the VE against clinical outcomes and deaths. The safety of the vaccines will be assessed using logistic regression models with an offset for the length of the risk period. Where possible, data will be meta-analysed across the UK nations. ETHICS AND DISSEMINATION: We obtained approvals from the National Research Ethics Service Committee, Southeast Scotland 02 (12/SS/0201), the Secure Anonymised Information Linkage independent Information Governance Review Panel project number 0911. Concerning English data, University of Oxford is compliant with the General Data Protection Regulation and the National Health Service (NHS) Digital Data Security and Protection Policy. This is an approved study (Integrated Research Application ID 301740, Health Research Authority (HRA) Research Ethics Committee 21/HRA/2786). The Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub meets NHS Digital's Data Security and Protection Toolkit requirements. In Northern Ireland, the project was approved by the Honest Broker Governance Board, project number 0064. Findings will be made available to national policy-makers, presented at conferences and published in peer-reviewed journals.

A randomised controlled trial of intrapleural balloon intercostal chest drains to prevent drain displacement.

BACKGROUND: Chest drain displacement is a common clinical problem that occurs in 9-42% of cases and results in treatment failure or additional pleural procedures conferring unnecessary risk. A novel chest drain with an integrated intrapleural balloon may reduce the risk of displacement. METHODS: A prospective randomised controlled trial comparing the balloon drain to standard care (12 F chest drain with no balloon) with the primary outcome of objectively defined unintentional or accidental chest drain displacement. RESULTS: 267 patients were randomised (primary outcome data available in 257, 96.2%). Displacement occurred less frequently using the balloon drain (displacement 5 of 128, 3.9%; standard care displacement 13 of 129, 10.1%) but this was not statistically significant (OR for drain displacement 0.36, 95% CI 0.13-1.0, Chi-squared 1 degree of freedom (df)=2.87, p=0.09). Adjusted analysis to account for minimisation factors and use of drain sutures demonstrated balloon drains were independently associated with reduced drain fall-out rate (adjusted OR 0.27, 95% CI 0.08-0.87, p=0.028). Adverse events were higher in the balloon arm than the standard care arm (balloon drain 59 of 131, 45.0%; standard care 18 of 132, 13.6%; Chi-squared 1 df=31.3, p<0.0001). CONCLUSION: Balloon drains reduce displacement compared with standard drains independent of the use of sutures but are associated with increased adverse events specifically during drain removal. The potential benefits of the novel drain should be weighed against the risks, but may be considered in practices where sutures are not routinely used.

United Kingdom Research study into Ethnicity And COVID-19 outcomes in Healthcare workers (UK-REACH): a retrospective cohort study using linked routinely collected data, study protocol.

INTRODUCTION: COVID-19 has spread rapidly worldwide, causing significant morbidity and mortality. People from ethnic minorities, particularly those working in healthcare settings, have been disproportionately affected. Current evidence of the association between ethnicity and COVID-19 outcomes in people working in healthcare settings is insufficient to inform plans to address health inequalities. METHODS AND ANALYSIS: This study combines anonymised human resource databases with professional registration and National Health Service data sets to assess associations between ethnicity and COVID-19 diagnosis, hospitalisation and death in healthcare workers in the UK. Adverse COVID-19 outcomes will be assessed between 1 February 2020 (date following first confirmed COVID-19 case in UK) and study end date (31 January 2021), allowing 1-year of follow-up. Planned analyses include multivariable Poisson, logistic and flexible parametric time-to-event regression within each country, adjusting for core predictors, followed by meta-analysis of country-specific results to produce combined effect estimates for the UK. Mediation analysis methods will be explored to examine the direct, indirect and mediated interactive effects between ethnicity, occupational group and COVID-19 outcomes. ETHICS AND DISSEMINATION: Ethical approval for the UK-REACH programme has been obtained via the expedited HRA COVID-19 processes (REC ref: 20/HRA/4718, IRAS ID: 288316). Research information will be anonymised via the Secure Anonymised Information Linkage Databank before release to researchers. Study results will be submitted for publication in an open access peer-reviewed journal and made available on our dedicated website (https://uk-reach.org/). TRIAL REGISTRATION NUMBER: ISRCTN11811602.

Real-time spatial health surveillance: Mapping the UK COVID-19 epidemic.

Introduction The COVID-19 pandemic has highlighted the need for robust data linkage systems and methods for identifying outbreaks of disease in near real-time. Objectives The primary objective of this study was to develop a real-time geospatial surveillance system to monitor the spread of COVID-19 across the UK. Methods Using self-reported app data and the Secure Anonymised Information Linkage (SAIL) Databank, we demonstrate the use of sophisticated spatial modelling for near-real-time prediction of COVID-19 prevalence at small-area resolution to inform strategic government policy areas. Results We demonstrate that using a combination of crowd-sourced app data and sophisticated geo-statistical techniques it is possible to predict hot spots of COVID-19 at fine geographic scales, nationally. We are also able to produce estimates of their precision, which is an important pre-requisite to an effective control strategy to guard against over-reaction to potentially spurious features of 'best guess' predictions. Conclusion In the UK, important emerging risk-factors such as social deprivation or ethnicity vary over small distances, hence risk needs to be modelled at fine spatial resolution to avoid aggregation bias. We demonstrate that existing geospatial statistical methods originally developed for global health applications are well-suited to this task and can be used in an anonymised databank environment, thus preserving the privacy of the individuals who contribute their data.

Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions.

INTRODUCTION: The emergence of the novel respiratory SARS-CoV-2 and subsequent COVID-19 pandemic have required rapid assimilation of population-level data to understand and control the spread of infection in the general and vulnerable populations. Rapid analyses are needed to inform policy development and target interventions to at-risk groups to prevent serious health outcomes. We aim to provide an accessible research platform to determine demographic, socioeconomic and clinical risk factors for infection, morbidity and mortality of COVID-19, to measure the impact of COVID-19 on healthcare utilisation and long-term health, and to enable the evaluation of natural experiments of policy interventions. METHODS AND ANALYSIS: Two privacy-protecting population-level cohorts have been created and derived from multisourced demographic and healthcare data. The C20 cohort consists of 3.2 million people in Wales on the 1 January 2020 with follow-up until 31 May 2020. The complete cohort dataset will be updated monthly with some individual datasets available daily. The C16 cohort consists of 3 million people in Wales on the 1 January 2016 with follow-up to 31 December 2019. C16 is designed as a counterfactual cohort to provide contextual comparative population data on disease, health service utilisation and mortality. Study outcomes will: (a) characterise the epidemiology of COVID-19, (b) assess socioeconomic and demographic influences on infection and outcomes, (c) measure the impact of COVID-19 on short -term and longer-term population outcomes and (d) undertake studies on the transmission and spatial spread of infection. ETHICS AND DISSEMINATION: The Secure Anonymised Information Linkage-independent Information Governance Review Panel has approved this study. The study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals.

Generating and Knowledge Framework: Design and Open Specification.

INTRODUCTION: The Information Aggregation (IA) component manages streaming and batch data deriving from a multitude sources in a scalable, efficient and reliable way to create Holistic Health Records (HHRs).Within this context, the IA component combines a number of diverse data sources into a common format and stores information in an available form to be used for analytics, simulations and decision making. AIM: The purpose of this paper is to provide an overview of the CrowdHEALTH project and the technical architecture of the CrowdHEALTH platform in order to put the aforementioned IA mechanism in context. This is followed by the design details and initial specifications of the first prototype of the IA component as well as its relationship with other components. METHODS: The micro-service approach can be used to perform information aggregation and to update HHRs in the CrowdHEALTH platform. Micro-services are a variant of the service-oriented architecture (SOA) where applications are structured as a collection of loosely coupled services with defined interfaces. RESULTS: Within the CrowdHEALTH architecture, the Information Aggregation component is situated between the Interoperability Layer and the CrowdHEALTH Datastore. The Information Aggregation component processes and aggregates interoperable data, before data aggregation in the HHRs and storage in the big datastore of CrowdHEALTH platform. The aggregation functions use big data management techniques and enhance the state of the art in specific areas such as the use of micro-services to perform synchronous aggregation operations on heterogeneous datasets. CONCLUSIONS: Although an initial version of the IA component was presented, the specifications and implementation level details will be further updated during the project's course.